Tag: Subsystems

Minneapolis: How do we partition a city into sub-systems?

By Matt Johnson

So far we’ve established the (3) systems’ axioms; we’ve touched on the notion of systems’ boundaries by using examples of cities; and we’ve established what a system’s behavior is by analyzing the labor force, average weekly wages, and unemployment rate of Minneapolis. Today, we are going to begin to partition the Minneapolis system into its respective subsystems and we are going to do it by ward.

In the next blog, we will decompose Minneapolis by zip-code. And in a future article, we will decompose Minneapolis’ wards into their respective subsystems – neighborhoods – which will introduce us to the notion of systems’ levels.

Minneapolis is a city with 413,651 residents as of July 1, 2016 according to the U.S. Census Bureau. Furthermore, those 413,651 residents obviously live in different parts of the city. Those parts of the city are called wards and Minneapolis has 13 Wards. According to Minneapolis City Government data, each ward contains about 32,000 residents, which of course varies every few years.

This means that each ward in Minneapolis contains about 32,000 residents; those residents interact with each other; and each ward has a function, which in this case is to provide political opportunity in voting and representation, and allocation of resources.

Thus, we have just shown that all 13 wards in Minneapolis satisfy the (3) systems’ axioms:

  1. A system consists of a set of elements.
  2. Elements in a system interact.
  3. A system has a function, or purpose.

Besides illustrating that these 13 wards are systems, we have also established that these wards are themselves subsystems of the general system of Minneapolis. This is because we have shown they satisfy the systems’ axioms, they are contained within Minneapolis, and they have established boundaries, i.e., political boundaries.

And this is a great place for us to dig a little deeper into the notion of boundary. Boundaries can be fuzzy or concrete; and boundaries can be regular or irregular. In the case of political boundaries, which are the wards we are observing, they are concrete and irregular. If we look at any of the 13 wards in Minneapolis, we can observe that the boundaries of the wards are well-defined, i.e., concrete. And we know this is because of the Minneapolis City Charter. But we can also observe that these boundaries are irregular. That is, they are not squares, rectangles, triangles, or circles.

In this short blog, we established that these 13 wards are subsystems of Minneapolis. We also established, with the help of the map, that the boundaries of these wards are concrete and irregular. As we keep moving forward, we will see that our new-found knowledge of systems will pay dividends when we begin to compare and contrast the different wards, neighborhoods, zip-codes, and other Minneapolis subsystems. And we will do this by adding a new tool to our systems’ took-kit – systems dynamics.

Let us now, as we have done before, attempt to disprove our systems’ notions and work in the tradition of natural philosophy until the next blog.


Matt Johnson is a blogger/writer for The Systems Scientist and the Urban Dynamics blog. He has also contributed to the Iowa State Daily and Our Black News. Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. 

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Analyzing a Crime Pattern of a General System

By Matt Johnson, The Systems Scientist

Crime is an important indicator of the attractiveness of a city in Urban Dynamics. This means it’s important to consider and recognize because it could and often does have a negative and adverse affect on a city as well as individual parts of a city.

Photo Courtesy of the City of Minneapolis
Photo Courtesy of the City of Minneapolis

Let us use rationale and data to guide our way and perceptions. We’ve seen patterns in previous articles that describe different systems’ behaviors in different parts of the city. For example, we’ve seen and compared the behavior of the foreclosure rates in the 4th and 5th Wards and the behavior of the foreclosure rate in the 2nd Ward.

It was clear from the data that the foreclosure rates of the 4th and 5th Wards closely mimicked the behavior of the foreclosures of the general system of Minneapolis. Conversely, it was clear that the foreclosure behavior of the 2nd Ward seemed to have a mind of its own, nor an attachment or relationship with the behavior of the general system of Minneapolis (See link below).

And as this author implicitly indicated in a recent article in Our Black News, the difference in unemployment between those in predominantly “black” neighborhoods and those in predominantly “white” neighborhoods is as much as 4 to 5 times if not more. Of course, years of data would allow this author to compile and analyze more precise systems’ behaviors with more accurate conclusions.

Table 1
Table 1

Making due with what we currently have, Table 1 shows us that the crime rate from 2015 follows a fairly normal distribution, i.e., Bell-curve. We also notice from the table that the crimes are skewed towards the 2nd half of the year. In other words, there are more crimes committed in the later half of the year than in the first half of the year. And finally, we can see that the month with the highest number of crimes for 2015 was July with 2,116; whereas, the month with the lowest number of crimes for 2015 was February with 1,144.

As we will see in future articles, this Bell-curve pattern was pretty much the same for 2013 and 2014. We will also notice the months for the lowest and highest numbers of crimes will remain the same; that is, February and July, respectively.

The good news is the fact that the number of overall crimes in the city has been decreasing from year to year, at least back to 2013. And although February and July remain the lowest and highest months for crime, respectively, the total number of crimes for each month decreased from 2013 to 2014 and from 2014 to 2015.

It will be clear to us over the next couple articles that the number of crimes in the general system of Minneapolis is trending downwards. This added together with the decreasing unemployment rate over the past few years and the decreasing foreclosure rate is certainly goods news for the residents of Minneapolis in general. However, we must ask ourselves some worthwhile questions as we always do.

How do the crime rates of the 13 Wards of Minneapolis compare to the crime rate of Minneapolis itself? Remember, the sub-systems of Minneapolis are being analyzed and compared to the general system of Minneapolis.

Another question, how do the crime rates of the respective neighborhoods compare to the crime rates of their parent wards and the crime rate of the city overall? Will there be similarities? Will there be differences? What type of crimes are being committed? Will the crime rates be higher in predominantly “black” neighborhoods? And finally, what else can be gleaned from such data? In other words, what does it say about the system?

For further exploration of this subject, explore Patterns of the 5th Ward: “Race”Patterns of the 5th Ward: Unemployment, Foreclosure Rates: Wards 2, 4, and 5 from 2006 to 2015.

**Remember, there is nothing more American than discourse. You are always welcome to post your comments, thoughts, and questions below. Feedback is always appreciated!



The Simple Behaviors of Cities

By Matt Johnson

Cities are complex systems with complex and chaotic behaviors, but yet those same systems as philosopher of science Michael Streven’s explains in his book Bigger than Chaos: Understanding Complexity through Probability can contain simple behaviors as well. As Strevens elucidates, “Simplicity in complex systems’ behavior is everywhere.”

Figure 1
Figure 1

As examples, he uses ecosystems, economic systems, the weather, chemical reactions, and societies to explain such simplicity. In his example of societies, he states

…the familiar positive correlation between a person’s family’s social status or wealth and that person’s success in such areas as educational achievement [is a simple behavior].

We have seen simple systems’ behaviors with the graphical information presented time and time again with respect to the systems research of the City of Minneapolis by Urban Dynamics. For example, in a previous post about the foreclosures in the general system of Minneapolis, we saw that although the total foreclosures in the city peaked out around 900 properties in 2008, there has been a fairly consistent decrease over the past 7 to 8 years. Explicitly this is an example of a simple behavior in the system and Figure 1 illustrates this simple behavior.

We have also been exposed to the simple behaviors of some of the subsystems of Minneapolis. For example, we learned that the foreclosure rates of the 2nd Ward in Southeast Minneapolis, and the 4th and 5th Wards in North Minneapolis exhibited different behaviors in their respective locations as illustrated in Figure 2. But adding a bit more systems language, philosophy, and science to our analysis, we now know that the respective behaviors in these subsystems are also simple in nature.

And finally, if we compare the simple behaviors between the general system of Minneapolis and the respective subsystems of Minneapolis, we can see that there are some differences and some similarities. The contrast of the systems’ rates and behavior can provide us with some worthwhile information.

Figure 1
Figure 2

For example, we see a decreasing foreclosure rate in Figure 1. The General Minneapolis System (let’s call it the GMS) is tending downwards towards the horizontal (the x-axis) of the graph. In addition, both the 4th and 5th Wards are exhibiting similar general systems behaviors in their respective subsystems. It appears as though the foreclosures of the GMS and the 4th and 5th Wards are converging if we compare Figure 1 and Figure 2.

As a consequence of this information, are we to assume that as the city goes, the 4th and 5th Wards go? In other words, does the behavior of the 4th and 5th Wards depend on the behavior of the GMS? Do the simple systems’ behaviors of the 4th and 5th Wards reflect the simple system’s behavior of the GMS? Why would we think this?

As we can also see from Figure 2, the 2nd Ward’s behavior is rather flat over the course of the ten years or so. The simple behavior of the 2nd Ward doesn’t seem to be influenced or dependent on the behavior of the GMS. As the GMS is doing its thing, the 2nd Ward is exhibiting completely different behavior. Why might this be?

We must caution ourselves first before we try to answer this question, or any other questions for that matter. We must caution ourselves before assuming too much from the data. If we try to extract more information from the data than we actually can, we risk drawing conclusions that make little sense. Moreover, our overreaching conclusions could have disastrous effects if applied to policy. This data has limits.

Cities can seem a bit overwhelming sometimes. At the ground level, they seem chaotic, and indeed they are. There are a plethora of interactions and activities taking place every second of the day. But the good news is that systems contain simple behaviors in all of the chaos. And the better news is that this simple behavior can be extracted from the chaos and analyzed to provide citizens and policy makers with some much-needed and worthwhile information.

For further reading on similar subject matter, I invite you to read The General System of Minneapolis: ForeclosuresForeclosure Rates: Wards 2, 4, and 5 from 2006 to 2015 and Patterns of the 5th Ward: “Race”.

Remember, you are always welcome to post your comments, thoughts, and questions below. Feedback is always appreciated.